Artificial intelligence, more commonly known as AI, is transforming many industries at breakneck speed. The sector of fast-moving consumer goods (FMCG) is no exception. The world of consumer packaged goods sold quickly and cheaply is being changed by technology that, while not necessarily inexpensive, is able to save money through the fast automation of processes and workflows.
To explain what is happening, let’s look at the connection between machine learning and Coca Cola vending machines. The fizzy drink behemoth today offers 4,000 drink options via the main Coke business and various brands it owns. Over a decade ago, 165 of those beverages began to be offered in a touchscreen vending machine called the Coca-Cola Freestyle, which gave consumers a chance to mix-and-match Coke branded products. A glorified soda fountain, the Freestyle machine could offer up to 200 variations on these products, mixing and dispensing drinks as required.
The pièce de résistance was that these machines were cloud-connected and AI-enabled. Data was being collected on what kind of mixtures customers were ordering from the Freestyle and used by Coca-Cola for market research for future products. From this process was born cherry-flavoured Sprite, a permanent and popular addition to the brand’s mammoth drink range.
Stories like this demonstrate why consumer goods is investing heavily in AI. As a recent GlobalData thematic research on AI in consumer goods reports, global AI platform revenue in consumer goods will grow from $1.2bn in 2019 to reach $3.5bn by 2024. This is above the market average of 20.8% that GlobalData predicts for the same time span.
For consumer goods, AI is fast becoming a way to utilise its data efficiently and work out what products their customers want, almost skipping traditional R&D stages entirely.
Beautiful machinations in consumer goods
Smart vending machines aren’t the only data-hungry devices that lurk amongst shoppers. If something is digital, then it’s able to collect data. Hook it online and that data can be shared. Allow machine intelligence to analyse that data and even the quietest highstreet becomes part of the AI revolution.
How well do you really know your competitors?
Access the most comprehensive Company Profiles on the market, powered by GlobalData. Save hours of research. Gain competitive edge.
Thank you!
Your download email will arrive shortly
Not ready to buy yet? Download a free sample
We are confident about the unique quality of our Company Profiles. However, we want you to make the most beneficial decision for your business, so we offer a free sample that you can download by submitting the below form
By GlobalDataIt’s not only drink brands who are benefitting from AI and customer interaction. Beauty brands are also among the biggest innovators in FMCG, with many of them combining AI with the equally hyped tech of extended reality .
L’Oréal’s augmented reality (AR) brand ModiFace offers tools to help both online and offline customers find the right product for their particular skin and hair requirements. In-store screens double as digital makeup mirrors, using AR to apply various shades in real-time. This is made possible by AI-powered analysis of data provided by makeup brands and L’Oréal’s photo database of 6,000 clinical images.
Due to Covid-19 restricting in-store consultations, numerous beauty companies are also investing in AI and AR. Startups like Nudest are using AI to find the right product for consumers regardless of skin tone, trained on selfies sent in by volunteers of all skin tones. Nudest’s Nudemeter tool has since been adopted by brands such as Nude Barre and Spktrm Beauty to expertly match customer to product. Any gaps in the market for those with less-catered skin tones will lead to new products, echoing the Coca-Cola Freestyle experiment.
Consumer or cookie?
AI effectively makes customers into R&D for brands, bypassing the middleman. As GlobalData analyst Sarah Coop tells Verdict: “AI tools are putting consumers at the centre of research and development. Companies can react to trends more quickly, identify innovative product opportunities, and reduce the time to market.”
Coop notes consumer data from brand interactions is being mined and analysed in the same way anonymised consumer data is mined on the internet. Brands though have to not lose sight of their responsibilities. L’Oréal is keen to stress that data compliance and ethics of data are “integrated by design” into ModiFace and do not allow identification of individuals.
But customers may not be fully aware of their rights when using AI-powered touchpoints, and may question providing data when already handing over their money at a vending machine. The prospect of possible tailored products may not make customers eager to engage with brands this way. Again, a Coca-Cola vending machine may provide one interesting avenue, in this case a quirky one-off known as the Dialekt-o-maten.
Available in Sweden during the summer of 2017, the Dialekt-o-maten invited people to attempt regional Swedish dialects in exchange for a free can of Coke. Various dialects were arranged on the machine’s front with a button below each one. The user would hit a button then repeat a phrase given by the machine in that same accent. The more accurate a user’s accent, the higher their chance of a free drink, as Python-based machine learning within the Dialekt-o-maten analysed voices for an audio fingerprint.
A harmless bit of fun and science, the Dialekt-o-maten was more of a marketing tool for Coca-Cola as opposed to an R&D experiment. But the stunt offers a valuable lesson in how to gather and test data through the promise of a free reward for the customer, something light years ahead of, say, submitting a survey participant into a prize draw with stacked odds. Not only could this make consumers feel less like internet cookies, but it adds a more human side to both data gathering and the potentials of AI.
Goods brands become tech ones
Gathering data on customers isn’t new for consumer brands. But how technology is transforming these brands is a new trend in the industry, with GlobalData analysts noting that more and more brands are snapping up AI startups.
“Consumer goods companies are not becoming tech companies yet, but it is only a matter of time,” says Coop. “One of the best ways to tech-enable a business, or excel in a theme like AI, is to acquire a company or startup that is already a forerunner in that field. Consumer goods companies can fast-track their tech capabilities by acquiring a company. The most high-profile FMCG tech acquisition was L’Oreal acquiring ModiFace in 2018. L’Oreal were ahead of the curve, and other FMCG companies should follow this example to future-proof their businesses.”
For businesses to keep growing in the 2020s, they need to be as clued in as possible to customer demands and they way they interact with their brand. Technology can bridge that gap between goods providers and the consumer, with AI being the figurative machine between both, allowing both parties to vend to one another.
“Companies that integrate AI in all areas of the value chain will be the most successful,” Coop adds. “FMCG companies must safeguard their businesses by investing in AI, because it will eventually become essential practice.”
Find the GlobalData Thematic Research: Artificial Intelligence (AI) in Consumer Goods report here.
